Unsupervised domain adaption (UDA) is a transfer learning task where the...
In this paper, we study phase retrieval under model misspecification and...
To train robust deep neural networks (DNNs), we systematically study sev...
Mutual knowledge distillation (MKD) improves a model by distilling knowl...
In this work, we address robust deep learning under label noise
(semi-su...
Loss functions play a crucial role in deep metric learning thus a variet...
Set-based person re-identification (SReID) is a matching problem that ai...
It is fundamental and challenging to train robust and accurate Deep Neur...
Label noise is inherent in many deep learning tasks when the training se...
The objective of deep metric learning (DML) is to learn embeddings that ...
Deep metric learning aims to learn a deep embedding that can capture the...